Role of urban green space structure and configuration in regulating land surface temperature in NCT Delhi using explainable artificial intelligence

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dc.contributor.authorKumar, Manish
dc.date.accessioned2026-03-27T09:51:55Z
dc.date.available2026-03-27T09:51:55Z
dc.date.issued2026
dc.description.abstractUrbanization-driven heat intensification poses a serious challenge to environmental sustainability and thermal comfort in megacities such as National Capital Territory (NCT) Delhi. The influence of green space structure and configuration on Land Surface Temperature (LST) remains under explored. This study presents a novel framework that integrates Fragstats-derived green space metrics and explainable artificial intelligence (XAI) to assess the spatio-temporal impact of green space structure and configuration on LST in NCT Delhi. The LST and nine green space metrics were derived using the Landsat-8 (OLI/TIRS) imagery. Three machine and deep learning models i. e., Gradient Boosting Machine (GBM), Distributed Random Forest (DRF), and Deep Learning (DL) were developed to regress and predict LST using H2O AutoML package in Rstudio environment. Among these, GBM produced the highest predictive accuracy (R 2 = 0.8859) and was therefore selected for further interpretation using XAI techniques such as SHapley Additive exPlanations (SHAP) and Individual Conditional Expectation (ICE) plots. Results show that fragmented green spaces intensify surface heating, while cohesive and well-connected green space corridors pro mote cooling through enhanced evapotranspiration and shading. The findings highlight that not only the amount but also the spatial configuration of vegetation determines its cooling efficiency. Areas in East Delhi (Shahdara, Seelampur) and North-West Delhi (Narela, Bawana, Rohini Extension), characterized by high fragmentation, experience higher temperatures, whereas contiguous green space corridors of Central and South Delhi exhibit stronger cooling benefits. These insights provide actionable guidance for urban planners and policymakers to prioritize cohesive green space development in future urban planning for climate adaptation and mitigation.
dc.identifier.urihttp://cuh.ndl.gov.in/handle/123456789/1857
dc.language.isoen
dc.titleRole of urban green space structure and configuration in regulating land surface temperature in NCT Delhi using explainable artificial intelligence
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